AI @ CSX
Summary
- CSX has progressively integrated AI technologies from 2016 onwards, starting with IoT-enabled machine learning for train delay analysis, advancing to AI-powered chatbots in 2024, and by 2025 leveraging cloud AI solutions like Microsoft Azure and Copilot to enhance real-time operations and customer service.
- The company has actively collaborated with research institutions and government agencies (e.g., Rutgers University, Federal Railroad Administration) to develop AI-driven safety systems such as trespassing detection and intruder learning, reflecting a strong focus on operational safety improvements.
- By mid-2025, CSX's AI adoption is mature and expanding, including investments in decentralized AI platforms and digital transformation initiatives that improve supply chain agility, predictive maintenance, and operational efficiency, positioning CSX as a leader in AI-driven railroad innovation.
VIBE METER
5 AI Use Cases at CSX
Safety Evaluation
Operational Efficiency
Safety Monitoring
Customer Support
Delay Prediction
Timeline
2025 Q3
CSX and industry partners focused on digitalization of railway transportation using AI-powered IoT, digital twin trains, edge computing, and human-centric AI testing to improve safety and operational efficiency.
- European Transport Research Review: Digitalization of railway transportation through AI-powered technologies
- Klover AI: Union Pacific's AI Strategy: Analysis of Dominance in Railroad
- Transportation Research Board: Integrating AI and edge computing for advanced safety at railroad crossings
- World Transit Research: Artificial intelligence-aided railroad trespassing detection case study
- ScienceDirect: Artificial intelligence-aided railroad trespassing detection study
- Computing Research Association: Human-centric AI testing and evaluation improves railroad safety
2025 Q2
CSX leveraged Microsoft Azure and AI solutions to transform rail operations with real-time data analytics, reduce derailments, and enhance supply chain agility using Microsoft Copilot.
2025 Q1
CSX and industry peers expanded AI use cases including predictive maintenance, automated yard checks, and optimized switching, with growing emphasis on generative AI benefits.
- BNSF: Eyes on AI: BNSF innovates to better serve our customers
- University of New Mexico: Right on track: Researchers use new tech to improve railroad safety
- Everest Railcar Services: The Rails Ahead: How AI is Revolutionizing the Railroad Industry
- CBS42: The Value Of Adopting Generative AI In The Freight Railroad Industry
2024 Q4: no updates
2024 Q3
Research and deployment of AI intruder learning systems and AI-powered camera technology enhanced railroad safety and hazard detection.
2024 Q2
Collaboration with Rutgers University to develop an AI-based railroad trespassing database demonstrated CSX's commitment to safety innovation.
2024 Q1
CSX introduced an AI-powered chatbot to streamline real estate inquiries, improving customer experience; industry reports highlighted AI as a catalyst for operational improvements.
2023 Q4: no updates
2023 Q3
AI concepts and machine learning gained prominence in the transportation industry, setting the stage for broader adoption.
2023 Q2: no updates
2023 Q1: no updates
2022 Q4: no updates
2022 Q3: no updates
2022 Q2: no updates
2022 Q1: no updates
2021 Q4: no updates
2021 Q3: no updates
2021 Q2: no updates
2021 Q1: no updates
2020 Q4: no updates
2020 Q3: no updates
2020 Q2: no updates
2020 Q1
Industry-wide adoption of AI and robotics began impacting railroad workers, signaling technological shifts in operations.
2019 Q4: no updates
2019 Q3: no updates
2019 Q2: no updates
2019 Q1: no updates
2018 Q4: no updates
2018 Q3: no updates
2018 Q2: no updates
2018 Q1: no updates
2017 Q4: no updates
2017 Q3: no updates
2017 Q2: no updates
2017 Q1: no updates
2016 Q4: no updates
2016 Q3: no updates
2016 Q2
CSX began its AI journey by implementing IoT-enabled machine learning to create a train delay index, quantifying trip failures and associated costs.